NSF award 2441633 · University of Kansas Center for Research Inc

CAREER: Embracing Uncertainty in High-Performance Computing Resource Scheduling: An Integrated Algorithmic and Machine Learning-based Approach

Final report due

28 January 2031

in 1,563 days · The award ends on 30 September 2030.

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award ending 2030-09-30 · Research.gov
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Extension request16 Aug 2030in 1398 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2030in 1433 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 September 2030.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2031.

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Award card

Award number: 2441633
Period of support: 1 Oct 2025 – 30 Sep 2030
Amount: $558,208
Awardee: University of Kansas Center for Research Inc, Lawrence, KS
Program: Software & Hardware Foundation, EPSCoR Co-Funding
Directorate: CSE

Abstract

Resource scheduling is a critical component of high-performance computing (HPC) systems. Despite extensive literature on scheduling, new challenges continue to arise due to advancements in hardware, software, and evolving models, metrics, and performance demands. Today’s HPC systems operate on an unprecedented scale, presenting significant challenges for resource management, particularly when facing uncertainty…

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